To solve this problem, this paper proposed a signal noise separation algorithm based on morphological gradient to separate signals from background noise by detecting edges of signals.
针对这一问题，提出了一种基于形态学梯度的信号噪声分离算法，通过检测信号的边缘实现信号噪声分离。
Wavelet Transfer (WT) is a powerful technique in signal separation. It is very easy for WT to improve the signal-to-noise (SNR) by separating the random noise and useful signal.
小波变换技术具有很强的信号分离能力容易把随机噪声从信号中分离出来，从而提高信号的信噪比。
Blind separation of sources based on higher order cumulants is applied to the separation between vibration signal and noise, which is important to diagnosi.
本文利用基于高阶累积量的盲信号分离方法，设计了相应算法，成功地从被噪声污染的信号中恢复源振动信号，从而可确保碰摩故障的检测和诊断能顺利进。
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